Technical Change and Model Specification: U.S. Agricultural Production
利用时间序列计量方法分析美国农业产出关系，发现传统模型高估统计精度并产生大量虚假结果，尤其是关于技术变迁的结论；在考虑数据时间序列特性后，技术变迁的偏误显著减少。
Abstract U.S. agricultural crop and livestock relationships are examined in the context of both duality and time‐series econometrics. Based on time‐series test results, cointegrated models are estimated. Traditional models generally overestimated the precision of statistical relationships and gave a considerable number of spurious results, particularly with regard to technical change. When time‐series properties of the data were addressed, there was much less evidence of bias in technical change. Model specification test results were sensitive both to the time‐series specification of the maintained model and its functional form. Preferred functional form depended on the choice criterion.